Ten weeks of data on the Commodity Futures Index are as follows.
7.36 7.40 7.54 7.56 7.61 7.52 7.53 7.70 7.61 7.55
(a)
Construct a time series plot. What type of pattern exists in the data?
a.The data appear to follow a seasonal pattern.
b.The data appear to follow a horizontal pattern.
c.The data appear to follow a trend and seasonal pattern.
d.The data appear to follow a cyclical pattern.
Correct: Your answer is correct.
(b)
Use trial and error to find a value of the exponential smoothing coefficient that results in a relatively small MSE. (Consider any MSE less than 0.01 to be relatively small.)
=

Part b: The trial and error is used to find the value of exponential smoothing coefficient that results in MSE= 0.009 which is less than 0.01.

The MSE in the first table is calculated using the average of the two previous years.

The MSE in the second table is calculated using the moving average

The MSE in the third table is calculated by using ∝= 0.4 and the value of alpha changes to different values as shown in the cell U20, V20 and W20.

The MSE is the mean squared error.

We find the error by subtracting forecast data from the actual data.

The forecasted data may be average of 2 years , moving average of 3 years or adding the multiplied chosen value of alpha with the actual data and the multiplied value of 1- ∝ with the forecasted value of data.

The error is then squared.

The squared error is then averaged which gives the MSE.

The values of ∝= 0.400641005, 0.40319659, 0.400641001 may give the best MSE values.

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